Question

I compared several diagnostic methods to a gold standard using Bland-Altman plots. Now I would graphically represent the difference in agreement between each method and the gold standard in one single plot. I’m trying to plot means, confidence intervals and variance derived from the various Bland-Altman plots as horizontal boxplots, but I don’t know I to do that.
I have a dataframe like this:

Method    LCL    mean    UCL    var
A         -5     4       15     27
B         -9     2       13     33
C         -8     4       16     36

Thank you very much for your help!

Corrado

Answer 1

You need to realize that a “true” boxplot is a specific type of plot based on non-parametric statistics, none of which you have offered. If you want to call it something else you are free to do so and you can use the bxp function to do the plotting. You need to create a matrix with 5 rows and 3 columns with the values for whisker and box parameters. You may be thinking that the variance could be used to construct standard deviation?

 dat <- read.table(text="Method    LCL    mean    UCL    var
 A         -5     4       15     27
 B         -9     2       13     33
 C         -8     4       16     36
 ", header=TRUE)
 dat$sdpd <- dat$mean + dat$var^0.5
 dat$sdmd <- dat$mean - dat$var^0.5
 dat
#------
  Method LCL mean UCL var      sdpd      sdmd
1      A  -5    4  15  27  9.196152 -1.196152
2      B  -9    2  13  33  7.744563 -3.744563
3      C  -8    4  16  36 10.000000 -2.000000
#----------
 bxpm <- with(dat, t(matrix(c(LCL, sdmd, mean, sdpd, UCL), 3,5)))
 bxpm
#----------
          [,1]      [,2] [,3]
[1,] -5.000000 -9.000000   -8
[2,] -1.196152 -3.744563   -2
[3,]  4.000000  2.000000    4
[4,]  9.196152  7.744563   10
[5,] 15.000000 13.000000   16

 bxp(list(stats=bxpm, names=dat$Method ), main="Not a real boxplot\n
                                                Perhaps a double dynamite plot?")